Aggregate production planning with workforce transferring plan for multiple product types

This paper presents the aggregate production planning for multiple product types where the worker resource can be transferred among the production lines. A mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A real situation of a manufacturing company was selected as a case study. The actual data was used to test and validate the proposed model. The optimal aggregate production plan provides the information on managing the available production capacity together with the useful workforce transferring plan. The obtained solutions were compared to those of another approach where the workers cannot be transferred among the production lines. The total cost is significantly reduced when the workers are allowed to transfer among the production lines.     

Decomposition of aggregate defective rate in batch production

In batch/short run production, changes in productmix (or inter-product demand) can have a significant impact on the overall process defective rate, but this effect neglected in process quality analysis. This paper describes the use of a decomposition technique to single out this effect and the effect associated with changes in real process performance. The technique allows both effects to be expressed in indices which conveniently summarize information in a more concise and is often usable form. The results of an application study using a set of batch/short-run production data are presented.     

A Lean transportation approach for improving emergency medical operations

Abstract

This paper extends the approach of Lean transportation to improve the performance of emergency medical processes (EMP) by adapting its main concepts into the main characteristics of the EMP environment. The paper is based on an inductive theory-building process initiated from a case study in the field of emergency medical services. The development of the suggested performance improvement approach triggered from an exhaustive analysis of a process involved and an exploratory review of the existing improvement approaches available. The process of concern can be described as a specialized transportation process, where human lives are at risk. Its characteristics led to a natural application of Lean transportation. The results include, a novel approach for improving the agility and efficient EMS processes. This is validated with an application for improving ambulance response times and turnaround times of the Red Cross operations located in Monterrey, Mexico. The approach proved to be an integrated scheme for identifying waste opportunities at a systems level. This characteristic is important to let operations management prioritize improvement efforts in a limited budget situation. This work suggests the application of the emerging Lean transportation approach for increasing the agility performance of EMS processes.     

An approach to learning from both good and poor factory performance in a Kanban-based just-in-time production system

In a JIT manufacturing environment it may be desirable to learn from an archived history of data that contains information that reflects less than optimal factory performance. The purpose of this paper is to use rule induction to predict JIT factory performance from past data that reflects both poor (saturated or starved) and good (efficient) factory performance. Inductive learning techniques have previously been applied to JIT production systems (Markham et al. , Computers and Industrial Engineering, 34 , 717-726, 1998; Markham et al. , International Journal of Manufacturing Technology Management, 11 (4), 239-246, 2000), but these techniques were only applied to data sets that reflected a well-performing factory. This paper presents an approach based on inductive learning in a JIT manufacturing environment that (1) accurately classifies and predicts factory performance based on shop factors, and (2) identifies the important relationships between the shop factors that determine factory performance. An example application is presented in which the classification and regression tree (CART) technique is used to predict saturated, starved or efficient factory performance based on dynamic shop floor data. This means that the relationship between the variables that cause poor factory performance can be discovered and measures to assure efficient performance can then be taken.     

Hierarchical production planning at a multiproduct multiprocessor fibreglass manufacturing facility

Abstract

Abstract. A hierarchical production planning model is developed for a forming facility of a major fibreglass manufacturer. The model establishes aggregate quarterly quantities for families of products, monthly disaggregate production quantities for end-items within these families, and a weekly sequencing schedule of end-items. A key feature of the planning system is its ability to decompose total set-up cost into primary and secondary components and to account appropriately for each component at a distinct level of the planning hierarchy. The mathematical programming formulations, the accompanying solution algorithms, and the results of their application to nine months of actual company demand and cost data are presented.     

The quality of service: An overall performance assessment for water utilities

Over the last decades, the delivery of water supply services has changed among regions and actors, in order to meet the changing needs. Those services can be balanced based on the relation between the obligations they must fulfill, the quality offered, and the associated price/value for money. Furthermore, due to the water services inherent characteristics, they are prone to poor quality of service (in general terms). Thus, global performance assessments are of paramount relevance under those constraints. In Portugal, the water regulator has developed a system of performance indicators (partial measures of performance) and, therefore, it is not possible to achieve the desired holistic performance evaluation (global measure). To enable such assessment, we propose an application based on the ELECTRE TRI-nC method to define quality of service categories and aggregate performance indicators. To obtain a coherent family of criteria (i.e., exhaustive, cohesive, and non-redundant) we apply an iso-preference logic. The results obtained are presented through a geographical information system allowing for a clearer visualization of the overall performance of water utilities. The method proposed can be considered a suitable decision support system and useful regulatory tool able to provide policy relevant outputs.     

Application of control charts in analytic hierarchy process

Vendor rating can be done using the Analytic Hierarchy Process (AHP) by a single decision maker or a group of decision makers. This approach may suffer from some drawbacks including bias in estimation process. The proposed methodology in this paper involves estimation by a group on an individual basis following the principle of anonymity. A control chart is constructed with an upper control limit and a lower control limit. Implementation ofthiscontrol chart will take into account the dynamic nature of vendor performance and also can be used for continuous monitoring of the vendor performance. This procedure can be used for a single vendor as well as for multiple vendor rating.     

Models for supply chain reengineering

The goal of this paper is to provide a first step in the development of a coherent set of modelling methods for supply chain reengineering. This paper shows that different fields of attention in supply chain management should be approached with different modelling methods. Three modelling methods are presented: the event process chain (EPC) method; the activity chain model (ACM) method; and the GRAI grid method (adjusted for supply chains). EPC modelling focuses on time relationships between primary processes/functions, and is customer oriented. ACM modelling focuses on functions/processes and information flows. GRAI focuses on decision structures and information flows. The three methods are described, and an application of the methods to a case study company is presented. This paper concludes with a comparison of the methods and a discussion of their applicability.     

Application of TOC/OPT rules in a medium sized shop

Abstract

Abstract. Theory of constraints (TOC) and optimized production technology (OPT) are frequently presented as the better options for production control systems. Despite this enthusiasm, there is very little literature on how these principles can be implemented in practice without having to resort to the expensive proprietary software. In this paper we present a case study in which the OPT/TOC ideas were implemented without using the software. Management's major concern was reduction of work in process and increased delivery performance. It was decided to test whether the ideas of OPT/TOC were applicable in this environment and more importantly to which extent these two performance measures could be improved. The paper reports on the methodology used to test the OPT/TOC ideas in this shop and presents some early results of improvement, as well as some new problems which arose due to the new approach.     

Improving control through effective performance measurement in SMEs

Research has demonstrated that the use of performance measures in SMEs (small to medium sized enterprises) is limited. Financial measures, which are required for examination by external stakeholders, are generally well developed. However, operational measures are typically ad hoc and lack formal structure. A structured approach to measuring perform ance in SMEs should improve strategic control. Current approaches, however, have proved inadequate for the specific requirements of the SME sector. A new process is presented for developing effective performance measurement in SMEs, which is tested through a case study. The aim of the process is to develop measures that drive operational performance towards the achievement of strategic objectives. The results of the case study demonstrate the potential of the process for improving strategic control and stimulating continuous improvement in SMEs.     

Managing Supply Chain Execution: Monitoring Timeliness and Correctness via Individualized Trace Data

Improvements in information technologies provide new opportunities to control and improve business processes based on real‐time performance data. A class of data we call individualized trace data (ITD) identifies the real‐time status of individual entities as they move through execution processes, such as an individual product passing through a supply chain or a uniquely identified mortgage application going through an approval process. We develop a mathematical framework which we call the State‐Identity‐Time (SIT) Framework to represent and manipulate ITD at multiple levels of aggregation for different managerial purposes. Using this framework, we design a pair of generic quality measures—timeliness and correctness—for the progress of entities through a supply chain. The timeliness and correctness metrics provide behavioral visibility that can help managers to grasp the dynamics of supply chain behavior that is distinct from asset visibility such as inventory. We develop special quality control methods using this framework to address the issue of overreaction that is common among managers faced with a large volume of fast‐changing data. The SIT structure and its associated methods inform managers on if, when, and where to react. We illustrate our approach using simulations based on real RFID data from a Walmart RFID pilot project.     

Application of Design for Six Sigma tools in telecom service improvement

Abstract

Six Sigma is a systematic methodology aiming at operational excellence. Under the general umbrella of Six Sigma, DMAIC and Design for Six Sigma are usually be implemented to improve product and process quality. Facing quality bottlenecks in traditional improvement projects, tools in Design for Six Sigma is an efficient way to achieve better results. In this paper, to meet the high-quality requirement of key clients, a telecom service system improvement project is illustrated by redesigning troubleshooting and service delivery processes in company Shanghai Telecom Co. Ltd. (ST) with the aid of some Design for Six Sigma tools. Company ST improved its service system performance and obtained significant economic benefits from this project implementation. Four key factors that affect the success of Design for Six Sigma tools application in improvement projects are discussed at last.     

Telepresence in cross-site business process simulation - lessons learnt in technology,social interaction and organizational learning

Re-engineering global business processes requires innovative methods for inter-organizational learning. This article describes and analyses an experimental telepresence process simulation that was applied to develop and train the cross-site New Product Introduction process of a global telecommunication company. Interactive, real-time audio and video connections over the Internet supported the process-oriented discussion between two groups in distant locations. Identical visual process charts and other information, projected on the walls of the two auditoriums, helped the two teams to discuss and understand the process. Audibility of the discussion was crucial for learning, but the visual 'talking heads' of the participants distorted concentration. Facilitation at both ends and local simulation periods smoothed the interaction and the imbalances between the locations. The simulation achieved positive effects in immediate learning and in motivation for change, although the telepresence caused some limitations. The ultimate goal, the feeling of real presence, was not reached. But when time gets more expensive, and travelling less preferable, telepresence simulation can be a feasible group-mode e-learning method for inter-organizational learning.     

Models,methods and tools for interorganizational logistics operations

Enterprise modelling is today one of the key techniques to improve the performances of an enterprise. This paper first defines enterprise modelling techniques as compared to BPR techniques. Then the latest developments in GRAI methodology are presented. Finally, examples of industrial applications are presented for three methods: GIM (GRAI Integrated Method) for re-engineering, GIMSOFT for the choice of an ERP software package and ECOGRAI for the design and implementation of performance indicator system.     

An approximate summarization method of process data for acquiring knowledge to improve product quality

This paper describes a machine learning approach for a manufacturing database. The method is presented in the Nb-Ti superconducting wire domain. A Nb-Ti superconducting wire is produced by iterating the drawing and heat treatment operations. The purpose is to obtain approximate summarization of process data that describes how a production schedule can be improved for better product quality. The method consists of the following steps: First, define a ranking function for a production schedule. Then, generate 'positive' and 'negative' instances for improving a production schedule by comparing a pair of schedules and their ranking values in the database. Using a machine learning technique, called 'ID3', a 'modification patterns' are obtained that generalize the data for better production quality. The final step is to extract approximate information from the induced patterns, which is both desirable for easier understanding by human experts and necessary to avoid being too much influenced by excessive details or disturbances. Two criteria are proposed, correctness and applicability indices, for this approximation.     

Honoring complexity in sustainable supply chain research: a rough set theoretic approach (SI:ResMeth)

Abstract

Sustainable supply chain management (SSCM) faces greater complexity because it considers additional stakeholder requirements, broader sustainable performance objectives, increased sustainable business practices and technologies, and relationships among those entities. These additional complexities make SSCM more difficult to manage and operate than traditional supply chains. Complex systems require new methods for research especially given reductionist research paradigms of modern science. Rough set theory (RST) can be a valuable tool that will help address complexity in SSCM research and practice. To exemplify RST usefulness and applicability, an illustrative application using sustainable supply chain practices (SSCP), and environmental and economic performance outcomes is introduced. The conceptual case provides nuanced insights for researchers and practitioners in mitigating and evaluating various SSCM complexities. RST limitations and extensions are introduced.     

The application of a performance management system in hospitals: A hypothetical example

Abstract

The central theme of this article is performance management, defined as activities of organizations aimed at an effective and efficient use of their human resources. The organization focused on in particular is the hospital. Three principles taken from motivation theory are dealt with which are basic to performance management: goal setting, feedback and reinforcement. Next, a recently developed procedure (Pritchard 1990, Pritchard et al. 1988, 1989) for the design of performance management systems is described. This procedure, ProMES: Productivity Measurement and Enhancement Systems, is explained using a team of ward nurses as a hypothetical example. In addition to the nursing wards example, other potential applications of the ProMES technique to several hospitals areas are mentioned. Finally, some conditions that should be fulfilled in order to successfully start a ProMES project are discussed.     

Knowledge sharing for innovation performance improvement in micro/SMEs: an insight from the creative sector

Abstract

As economies become more reliant on innovative, knowledge-intensive firms, understanding the interaction between knowledge and improving innovation performance is increasingly important. Although most UK businesses are micro, small or medium-sized enterprises (micro/SMEs), knowledge management research has tended to focus on large companies Knowledge sharing can be critical for innovation performance, especially for smaller players with limited resources. Our study presents an insight from micro/SMEs operating in the highly knowledge-intensive and innovative games/entertainment software development sector. Using a mixed method approach, we investigate knowledge sharing and its contribution to firm innovation performance improvements. Our findings suggest that micro/SMEs are at the forefront of the creative sector precisely because of their smaller size. Our study reveals evidence of knowledge donation but limited evidence of knowledge collection in the knowledge sharing process. We develop a model highlighting the importance of industry context, individual knowledge and organizational size in knowledge sharing for innovation performance.     

Green and lean: a Gemba–Kaizen model for sustainability enhancement

Abstract

Despite the encouraging results obtained from the application of Green Lean, organizations have found the integration of Green and Lean, and their implementation as an integrated approach, challenging. This paper therefore presents a model for integrating Lean and Green based on the Gemba-Kaizen approach. The proposed model was developed on the basis of a through literature review on Gemba and Kaizen, conducted on peer reviewed journal articles and pragmatic books, and the more than 40 years of accumulated experience of the authors as academics, researchers, industrialists and consultants. The model was validated through two cases study in the aerospace and automotive industries. The results showed that the proposed model helped the case organizations to reduce the consumption of resources and improve their environmental performance. The proposed model can be the basis for further research on Lean and Green, contributing to help organizations to improve their sustainability performance.     

Constraint-based model for the cyclic multi-hoists scheduling problem

This article presents a method for the resolution of a material handling scheduling problem. The case studied is a real industrial problem. It consists of finding a cyclic schedule for hoist movements in a treatment surface shop. In this kind of facility, several hoists are used for all the handling operations and they have to share common zones. Then it is necessary to control that there is no collision. The mathematical formulation of the problem is based on a combination of disjunctive constraints. The constraints describe either movement schedule or collision avoidance. The resolution procedure presented identifies all the collision configurations and then uses a branch and bound-like algorithm to find the optimal solution of a given problem. The language chosen for our implementation is the constraint logic programming language: Prolog IV, which is able to solve constraints with rational variables. It actively uses the constraint propagation mechanism that can be found in several languages.